Comparison between the ages for the genders (after controlling for type)

Questions

• What are the differences between the ages for the different genders?
• Do we observe the same changes as globally?

Age effect - General Questions

• What are the differences between the ages?
• Which genes and pathways are differentially expressed between 8w and 52w, between 52w and 104w, between 8w and 104w? Are they the same? Is there a gradient?
• Are they different for the two genders?
• Are they different for the two types?

Loads

Libraries and functions

==========================================================================
*
*  Package WGCNA 1.63 loaded.
*
*    Important note: It appears that your system supports multi-threading,
*    but it is not enabled within WGCNA in R. 
*    To allow multi-threading within WGCNA with all available cores, use 
*
*          allowWGCNAThreads()
*
*    within R. Use disableWGCNAThreads() to disable threading if necessary.
*    Alternatively, set the following environment variable on your system:
*
*          ALLOW_WGCNA_THREADS=<number_of_processors>
*
*    for example 
*
*          ALLOW_WGCNA_THREADS=4
*
*    To set the environment variable in linux bash shell, type 
*
*           export ALLOW_WGCNA_THREADS=4
*
*     before running R. Other operating systems or shells will
*     have a similar command to achieve the same aim.
*
==========================================================================


Allowing multi-threading with up to 4 threads.

preparing gene to GO mapping data...
preparing IC data...
preparing gene to GO mapping data...
preparing IC data...
preparing gene to GO mapping data...
preparing IC data...

Data

Stats

	Wald padj < 0.05	LFC > 0 (Wald padj < 0.05)	LFC < 0 (Wald padj < 0.05)
52w VS 8w (F)	11.00	6.11	4.89
52w VS 8w (M)	2.06	1.26	0.80
104w VS 8w (F)	8.89	5.18	3.70
104w VS 8w (M)	17.89	9.29	8.60
104w VS 52w (F)	1.40	0.82	0.58
104w VS 52w (M)	18.69	9.53	9.16

Differentially expressed genes

Warning message in grep(txdbPattern, installedPackages):
“argument 'pattern' has length > 1 and only the first element will be used”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in grep(txdbPattern, installedPackages):
“argument 'pattern' has length > 1 and only the first element will be used”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in grep(txdbPattern, installedPackages):
“argument 'pattern' has length > 1 and only the first element will be used”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in grep(txdbPattern, installedPackages):
“argument 'pattern' has length > 1 and only the first element will be used”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in grep(txdbPattern, installedPackages):
“argument 'pattern' has length > 1 and only the first element will be used”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in grep(txdbPattern, installedPackages):
“argument 'pattern' has length > 1 and only the first element will be used”Warning message in pcls(G):
“initial point very close to some inequality constraints”

Counts

52w != 8w or 104w != 8w or 104w != 52w for F with abs(FC) > 2

52w != 8w or 104w != 8w or 104w != 52w for M with abs(FC) > 2

Genes with 52w != 8w or 104w != 8w or 104w != 52w for M or F and at least one FC > 2

Comparison of the numbers per types

Differentially expressed genes

Some explanation (specially for the gender difference in microglia aging)

Differentially more expressed genes

Differentially less expressed genes

DEG into gene co-expression network

• White: up-regulated
• Black: down-regulated

52w VS 8w

Female

Male

104w VS 52w

Female

Male

GO analysis

Biological process

Dot-plot with the most over-represented BP GO (20 most significant p-values for the different comparison)

Network based on description similarity

52w VS 8w

F

M

104w VS 52w

F

M

Cellular components

Dot-plot with the most over-represented CC GO (20 most significant p-values for the different comparison)

Molecular functions

Dot-plot with the most over-represented MF GO (20 most significant p-values for the different comparison)

KEGG pathways

[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."

Warning message in file.rename(from = paste("mmu", cat, ".pathview.multi.png", sep = ""), :
“cannot rename file 'mmu00533.pathview.multi.png' to '../results/dge/age-effect/age_gender/over_repr_kegg/mmu00533.pathview.multi.png', reason 'No such file or directory'”

[1] "Note: 16 of 6572 unique input IDs unmapped."

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limit_output extension: Maximum message size of 10000 exceeded with 10098 characters

[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."
[1] "Note: 16 of 6572 unique input IDs unmapped."

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Gender differences in aging

Question: Is there differences in aging between gender? Is there really a delay for some genes in male?

	52w vs 8w for F	52w vs 8w for M	104w vs 52w for F	104w vs 52w for M	Gene number
Set 1	!=	==	==	!=	729
Set 2	==	!=	!=	==	9

	Gene number
Set 1	729
Set 2	9

Genes with differential expression delayed in male

Genes (set 1):

• Differentially expressed between 52w and 8w in F
• Not differentially expressed between 104w and 52w in F
• Not differentially expressed between 52w and 8w in M
• Differentially expressed between 104w and 52w in M
• No criteria for 104w vs 8w in both F and M

Can't find mm10/geneSymbol length data in genLenDataBase...
Warning message in grep(txdbPattern, installedPackages):
“argument 'pattern' has length > 1 and only the first element will be used”Found the annotaion package, TxDb.Mmusculus.UCSC.mm10.knownGene
Trying to get the gene lengths from it.
Fetching GO annotations...
For 195 genes, we could not find any categories. These genes will be excluded.
To force their use, please run with use_genes_without_cat=TRUE (see documentation).
This was the default behavior for version 1.15.1 and earlier.
Calculating the p-values...
'select()' returned 1:1 mapping between keys and columns
Fetching GO annotations...
For 4389 genes, we could not find any categories. These genes will be excluded.
To force their use, please run with use_genes_without_cat=TRUE (see documentation).
This was the default behavior for version 1.15.1 and earlier.
Calculating the p-values...

       GO KEGG
over  345   12
under 152    7

52w VS 8w (F) > 0 and 104w VS 52w (M) > 0

[1] 186

	Pearson's product-moment correlation

data:  mat[, 1] and mat[, 2]
t = 34.483, df = 184, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.9083259 0.9475915
sample estimates:
      cor 
0.9305874 

29

52w VS 8w (F) > 0 and 104w VS 52w (M) < 0

[1] 136

	Pearson's product-moment correlation

data:  mat[, 1] and mat[, 2]
t = -26.39, df = 134, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.9393075 -0.8836611
sample estimates:
       cor 
-0.9157734 

17

52w VS 8w (F) < 0 and 104w VS 52w (M) > 0

[1] 267

	Pearson's product-moment correlation

data:  mat[, 1] and mat[, 2]
t = -8.3658, df = 265, p-value = 3.45e-15
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 -0.5471083 -0.3566042
sample estimates:
       cor 
-0.4570828 

117

52w VS 8w (F) < 0 and 104w VS 52w (M) < 0

[1] 140

	Pearson's product-moment correlation

data:  mat[, 1] and mat[, 2]
t = 16.17, df = 138, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
 0.7428457 0.8595714
sample estimates:
      cor 
0.8090422 

64

Summary

Genes with differential expression delayed in female

Genes (set 2):

• Not differentially expressed between 52w and 8w in F
• Differentially expressed between 104w and 52w in F
• Differentially expressed between 52w and 8w in M
• Not differentially expressed between 104w and 52w in M
• No criteria for 104w vs 8w in both F and M

0